34 software-defined-networks PhD scholarships at Technical University of Munich in Germany
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on an important topic in a well-funded multi-disciplinary international training network. The training involves multiple activities, in addition to your research, and secondments across our partners. Overview
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control software and machine learning expert. How you will support us: ▪ You will take on responsibilities in the field of control and operation of high-coherence superconducting quantum circuits, with a
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11.11.2024, Wissenschaftliches Personal In the project “BIG-ROHU” (BIG Data - Rotor Health and Usage Monitoring), a system is being developed which provides information on both the health and the actual stress of helicopter components using a data-based as well as a physics-based approach. In...
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15.05.2021, Wissenschaftliches Personal The chair of Software Engineering for Business Information Systems (sebis) at the Technical University of Munich is looking for an excellent candidate for a
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-situ measurement network and perform terrestrial laser scanning, analyzing microclimate data and their relation to forest structure, and using optical satellite time series and radiative transfer models
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networks involved in CHC perception, particularly in the context of prezygotic reproductive isolation within a species complex of parasitoid wasps (Nasonia). Our previous research has already deciphered
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to be developed. One promising research direction is the use of physics-informed deep learning, such as physics-informed neural networks or deep neural operator networks. Tasks: Work in a team on national
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European Training Network consortium. You will benefit from a team approach, integrated international mobility, high level subject and transferable skills development oriented to your future employment in
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Science Hands-on work experience in an innovative high-tech startup operating at the intersection of AI, healthcare, life sciences, data science, and software development The chance to actively contribute
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, supportive international scientific network • A diverse and inclusive working environment • Extensive advanced training opportunities Application Process Please apply by sending one PDF containing (a) a short